code: def forward(self, x_noisy, t, cond, return_ids=False):
      if isinstance(cond, dict):
          # hybrid case, cond is exptected to be a dict
          pass
      else:
          if not isinstance(cond, list):
              cond = [cond]
          key = (
              "c_concat"
              if self.conditioning_key == "concat"
              else "c_crossattn"
          )
          cond = {key: cond}
      x_recon = self.apply_step(x_noisy, t, **cond)
      return x_recon
  
file_path: NeMo/nemo/collections/multimodal/models/text_to_image/dreambooth/util.py
imports: from functools import partial
  import numpy
  import torch
  import torch.nn
  from nemo.collections.multimodal.modules.stable_diffusion.diffusionmodules.util import extract_into_tensor, make_beta_schedule
  from nemo.collections.multimodal.parts.stable_diffusion.utils import default, exists
  from nemo.core.classes.common import Serialization
label_desc: Use image node_id 2 for calling the DiffusionWrapper obj's underlying member method code with example usage: obj.forward(x_noisy, t, cond, return_ids) and returns: x_recon